834,500 research outputs found

    Not all paths lead to Rome: Analysing the network of sister cities

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    This work analyses the practice of sister city pairing. We investigate structural properties of the resulting city and country networks and present rankings of the most central nodes in these networks. We identify different country clusters and find that the practice of sister city pairing is not influenced by geographical proximity but results in highly assortative networks.Comment: 7 pages, 4 figure

    NETSCAPE - Europe and the Evolving World City Network

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    This paper focuses on the interdependencies between firms and spatial networks (nodes and linkages) at different European spatial scales. The paper is structured into two parts: (1) Conceptualization; (2) Empirical Analysis. Part (1) consists of three chapters conceptualizing various scales of city-firm networks. The first concerns the macro scale, discussing the development of specific networks within the globalization process. The second analyses the mezzo level of European networks and their national to supranational transformation. On the micro level Rotterdam's internal and external network is conceptualized. Part (2) empirically reveals the European city-firm network at mezzo and micro scales, based on datasets including the top 100 EU multinationals, their affilates/subsidiaries and the city locations of all these firms. Chapter one analyses the mezzo scale, showing various hierarchies of city-firm interdependencies, for the sectors of manufacturing, trade, information, public services and basic materials. The second chapter analyses the relative position of Rotterdam within this interscalar network, by specifically investigating its internal and external city-firm networks. From this Rotterdam's existing strengths and weakenesses, and possible future implications are determined.

    Complex Network Tools to Understand the Behavior of Criminality in Urban Areas

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    Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis process, i.e. from data preparation to a deep analysis of criminal communities. Furthermore, the "toolset" available for those works is not complete enough, also lacking techniques to maintain up-to-date, complete crime datasets and proper assessment measures. In this sense, we propose a threefold methodology for employing complex networks in the detection of highly criminal areas within a city. Our methodology comprises three tasks: (i) Mapping of Urban Crimes; (ii) Criminal Community Identification; and (iii) Crime Analysis. Moreover, it provides a proper set of assessment measures for analyzing intrinsic criminality of communities, especially when considering different crime types. We show our methodology by applying it to a real crime dataset from the city of San Francisco - CA, USA. The results confirm its effectiveness to identify and analyze high criminality areas within a city. Hence, our contributions provide a basis for further developments on complex networks applied to crime analysis.Comment: 7 pages, 2 figures, 14th International Conference on Information Technology : New Generation

    Networks and Cities: An Information Perspective

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    Traffic is constrained by the information involved in locating the receiver and the physical distance between sender and receiver. We here focus on the former, and investigate traffic in the perspective of information handling. We re-plot the road map of cities in terms of the information needed to locate specific addresses and create information city networks with roads mapped to nodes and intersections to links between nodes. These networks have the broad degree distribution found in many other complex networks. The mapping to an information city network makes it possible to quantify the information associated with locating specific addresses.Comment: 4 pages, 4 figure

    On the Perturbation of Self-Organized Urban Street Networks

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    We investigate urban street networks as a whole within the frameworks of information physics and statistical physics. Urban street networks are envisaged as evolving social systems subject to a Boltzmann-mesoscopic entropy conservation. For self-organized urban street networks, our paradigm has already allowed us to recover the effectively observed scale-free distribution of roads and to foresee the distribution of junctions. The entropy conservation is interpreted as the conservation of the surprisal of the city-dwellers for their urban street network. In view to extend our investigations to other urban street networks, we consider to perturb our model for self-organized urban street networks by adding an external surprisal drift. We obtain the statistics for slightly drifted self-organized urban street networks. Besides being practical and manageable, this statistics separates the macroscopic evolution scale parameter from the mesoscopic social parameters. This opens the door to observational investigations on the universality of the evolution scale parameter. Ultimately, we argue that the strength of the external surprisal drift might be an indicator for the disengagement of the city-dwellers for their city.Comment: 22 pages, 4 figures + 1 table, LaTeX2e+BMCArt+AmSLaTeX+enote

    Using Delay Tolerant Networks as a Backbone for Low-cost Smart Cities

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    Rapid urbanization burdens city infrastructure and creates the need for local governments to maximize the usage of resources to serve its citizens. Smart city projects aim to alleviate the urbanization problem by deploying a vast amount of Internet-of-things (IoT) devices to monitor and manage environmental conditions and infrastructure. However, smart city projects can be extremely expensive to deploy and manage. A significant portion of the expense is a result of providing Internet connectivity via 5G or WiFi to IoT devices. This paper proposes the use of delay tolerant networks (DTNs) as a backbone for smart city communication; enabling developing communities to become smart cities at a fraction of the cost. A model is introduced to aid policy makers in designing and evaluating the expected performance of such networks. Preliminary results are presented based on a public transit network data-set from Chapel Hill, North Carolina. Finally, innovative ways of improving network performance in a low-cost smart city is discussed.Comment: 3 pages, accepted to IEEE SmartComp 201